Triple

T32220122
Position Surface form Disambiguated ID Type / Status
Subject Temple of the Masks E823039 entity
Predicate maskCountApproximate P173850 FINISHED
Object multiple large masks LITERAL FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: multiple large masks | Statement: [Temple of the Masks, maskCountApproximate, multiple large masks]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: maskCountApproximate
Context triple: [Temple of the Masks, maskCountApproximate, multiple large masks]
  • A. mineCountApproximate
    Indicates that the number of mines associated with an entity is estimated or roughly counted rather than known exactly.
  • B. lapCountApproximate
    Indicates that the recorded number of laps is an estimate rather than an exact, precise count.
  • C. junctionCountApprox
    Indicates an approximate count of junctions or connection points involved in or associated with the given entities.
  • D. prototypeCountApproximate
    Indicates that the number of prototypes involved is an estimated or approximate count rather than an exact value.
  • E. hasApproximateMemberCount
    Indicates that an entity is associated with a group or collection for which only an estimated or non-exact number of members is known.
  • F. None of above. chosen

Provenance (4 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69f3490b4f948190b99e4f999f5be25f completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6bbc4129481909d12bf4d5723dd3b completed May 3, 2026, 3:06 a.m.
PD Predicate disambiguation batch_69f6b6293188819080d5041ca0adb969 completed May 3, 2026, 2:42 a.m.
PDg Predicate description generation batch_69f6b960ca4081909a77690c2b122f5e completed May 3, 2026, 2:56 a.m.
Created at: May 1, 2026, 12:38 a.m.